REPRODUCING THE TABLES AND FIGURES IN THE PAPER:
To reproduce the results reported in the tables and figures of the paper run the stata 
program (do-file) Regressions_paper_final.do. This paper uses the Stata database 
credit_chains_final.dta. A comma-separated version of the database is also included. The 
program creates a series of comma-separated files containing the tables reported in the 
paper. The name of each file is the table number in the paper. Thus, the file containing 
Table 4 is called Table4.csv. The program also creates a database with the distances 
between industry pairs (Distances_Industry_pairs.dta), a database with the main 
coefficient obtained after dropping one country and one industry at a time, and a text file 
with tables containing the summary statistics reported at the beginning of the paper.
The final set of results was obtained using Stata 10, but the code should also work on 
Stata 9 and 11.
The description of the variables in the credit_chains.dta database is the following 
(Acronyms: PWT = Penn World Tables 6.1, Heston et al. (2002); WDI: World 
Development Indicators, World Bank (2007); WS: Worldscope).

***************** MAIN IDENTIFIERS**********************************
wbcode	World Bank Country Code
ind1		Isic code first industry
ind2		Isic code second industry
ind_ij		Combination of Isic codes of both industries
***************** MEASURES OF CORRELATION************************
corr		Correlation of growth rates of value-added (80-03)
corrHPva	Correlation of HP filtered real value added
corriip		Correlation of growth of Index of Industrial Production
corr_t		log(corr + 1) - log(1-corr)
corr_rob	Robust measure of correlation of VA growth (using robust regression 
weights)
***************** CONTROLS ***************************
nestab1	Number of establishments industry 1
nestab2	Number of establishments industry 2
lognestab1	log (nestab1)
lognestab2	log (nestab2)
share1		Average share of manufacturing value added industry 1
share2		Average share of manufacturing value added industry 2
gth_vareal1	Average growth va ind 1 80-03
sdgvar1	Std. growth va ind 1 80-03
gth_vareal2	Average growth va ind 2 80-03
sdgvar2	Std. growth va ind 2 80-03
gth_iip1	Average growth index of industrial production industry 1
sdgth_iip1	Std. deviation growth index of industrial production industry 1
gth_iip2	Average growth index of industrial production industry 2
sdgth_iip2	Std. deviation growth index of industrial production industry 2
*****************SIMPLE DISTANCE MEASURES************************
buy		Buy distance between industries 1 and 2 defined as in Dupor (2004)
sell		Sell distance between industries 1 and 2 defined as in Dupor (2004)
*****************SYMMETRIC DISTANCE MEASURES*******************
rdems		Dem as in Shea correl. form only manufact.
********MEASURES OF FINANCIAL AND OVERALL 
DEVELOPMENT********
rgdpl8000	Average Real GDP per capita (PPP) 1980-2000 (PWT)
loggdp8000	log Average Real GDP per capita (PPP) 1980-2000 (PWT)
logpvtc8000	log private credit to GDP 80-00 (Beck et al. 2000)
stmktcap8000	Average stock market capitalization 80-00
sdgth_rgdpl8000	Std dev growth real GDP per capita (rgdpl) 1980-2000
logkapw8099	log Average capital per worker 80-99 from PWT (extended)
logopenwdi8000	log openness (total trade/GDP) WDI average 80-00
************MEASURES OF TRADE CREDIT USE***********
InvPaymax	Payables Financing: InvPay if available, othw. InvPay_all, otherwise 
InvPayturn1
InvPay		Payables Financing (Inverse Payables Turnover) median manuf >10 WS
InvPay_all	Payables financing, median all industries >10 WS
InvPayturn1	Median payables financing in the country (Wscope). All industries no min 
# firms
Stdmax	Std if available, otherwise Std_all, otherwise Stdbtpay
Std		Std to Pay, median manuf >10 WS
Std_all		Std to Pay, median all industries >10 WS
Stdbtpay	Median short term debt to payables in the country (from Wscope) 
quality		Quality InvPaymax data (manuf>10, all>10, all)
pctile_InvPaymax	10 quantiles of InvPaymax
pctile_DemPayCC_inv 20 quantiles of DemPayCC_inv
extendedsample	44 countries with data on either Paymax or Stdmax
********** MODEL MATRICES DISTANCE AND TCRED USE ***************
DemPayCC_inv	Model Matrix with Credit Chain using Dem and Inverse Payturn
DemStdpayCC	Model Matrix with Credit Chain using Dem and Stdbtpay
DemInvPayCC_c05	Model Matrix by country Built using Dem and Inverse Payturn
DemPayCCUK_inv	Model Matrix with Credit Chain using Dem and Inverse Payturn
DemPayCC_test	Model Matrix with Credit Chain using Dem and Payturn
***************** OTHER IND. CHAR TO DETERMINE DISTANCE 
***********
exf80_2	External financial dependence all firms 80-89
exf80_1	External financial dependence all firms 80-89
distance_exf80	abs( exf80_2 - exf80_1)
gini1		Gini coef. of the share of intermediate inputs in ind. 1
gini2		Gini coef. of the share of intermediate inputs in ind. 2
distancegini	abs(gini2-gini1)
capemp80_1	Average capital per employee (Cstat) in industry 1 in 80s
capemp80_2	Average capital per employee (Cstat) in industry 2 in 80s
distancecapemp	abs( capemp80_2 - capemp80_1)
invsa_1	Median Inventory to sale ratio of industry 1 in 80s
invsa_2	Median Inventory to sale ratio of industry 2 in 80s
distinvsa	abs( invsa_1- invsa_2)
dur1		Industry 1 durable
dur2		Industry 2 durable
distdur		abs(dur1-dur2)
***************** Other measures of IO relations **********************
DemVar	Model Matrix using Dem relative variances
BPay_inv	Model matrix based on 1st round effects and Inverse Payturn
*********************Material Cost Correction***********************
DemPayCC_invmat	Model Matrix with Credit Chain using Dem and Paymat
InvPayMatmax	InvPaymax*Mcost2cgs, Mcost2cgs_ws if available, othw. 
Mcost2cgs_ica
*******Alternative Measures of InvPay***********************
InvPay_amadeus	Payables Financing (Amadeus 2003 or 2007 if 2003 not available)
INVPAY	Inverse Payables Turnover ratio from regression within 
manufacturing
*******IO Measures of forward and backward linkages*******************
BackwdPayCC	Backward Linkages IO matrix with Credit Chain using Cost and 
Inverse Payturn

OBTAINING THE VARIABLES CONTAINED IN  THE MAIN DATABASE
With a few exceptions, the variables contained in the main database do not come directly 
from other sources but are generated from raw data sources by other programs that are 
part of the project. The description that follows describes how the main variables were 
produced. All the programs (do files) are included as part of this documentation. The 
processed databases produced by these programs and that contain the variables in the 
main database are also included. Notice that these intermediate databases may also 
contain some additional variables that were later not used in the paper. When possible, the 
databases used as input for these programs are also included, but many of the raw 
databases used, such as Worldscope, Compustat, and Amadeus, are proprietary and their 
contents cannot be distributed as part of the documentation of this paper. The following 
list contains information on how to access these proprietary databases:
*	Worldscope is a product of Thompson Reuters and purchase information can be 
obtained in their website at 
http://thomsonreuters.com/products_services/financial/financial_products/a-
z/worldscope_fundamentals/
*	The version used in this paper is the one corresponding to the 2006 version of the 
Worldscope CD. Newer versions will differ in coverage.
*	Compustat is a product of Standard & Poors and information on accessing it can 
be obtained at http://www.standardandpoors.com/products-services/capitaliq-
compustat/en/us. The data items I use in the paper was accessed through the 
Wharton Research Data Services (WRDS) in 2001.
*	Amadeus is a product of Bureau Van Dijk. Information on how to purchase 
access to the data is available at http://www.bvdinfo.com/Products/Company-
Information/International/Amadeus.aspx . The data I use come from the 2003 and 
2007 versions of the database.
*	Indstat (Industrial Statistics) is a database produced by the United Nations 
Industrial Development Organization (UNIDO). Information on accessing the 
data is available at http://www.unido.org/index.php?id=1000327 . This paper uses 
the 2005 edition of the database, including data at the 3-digit ISIC classification 
Revision 2.

There are four sets of variables in the main database that were created by different blocks 
of programs:

1.	Correlations between value-added growth and industrial production growth 
across countries and industry pairs, shares of manufacturing output corresponding 
to each industry, number of establishments, etc.
2.	Trade credit use measures for each country (also at the industry level when 
available)
3.	Trade credit measures for the US, overall and industry level.
4.	Measures of credit-chain distances.

THE CONSTRUCTION OF THE VARIABLES IN EACH OF THESE BLOCKS IS 
EXPLAINED BELOW

1.	CORRELATIONS, ETC.

As explained in the paper, these variables were constructed using data from the UNIDO 
Indstat 2005, 3-digit ISIC database. The database is proprietary, so it is not included as 
part of this documentation. There are two steps involved in the creation of these variables. 
*	The first step is the computation of growth rates for real value added, shares, 
etc. This is done by the stata program crea_growth_rates_unido_2005.do. The 
input file is a stata file with the raw data unido_2005_3d.dta. The output file 
is growth_rates_unido_3d_2005.dta. This output file still has plenty of 
information at the country-industry-year level, so it is too close to the original 
data and cannot be distributed either. The do file that create this database is 
included for those who have access to UNIDO Indstat 2005 3-digit ISIC 
Revision 2.
*	The second step is to use the data in growth_rates_unido_3d_2005.dta to 
compute the average correlations between industry pairs, average number of 
establishment of each industry in each country, etc. as explained in the paper. 
These different variables are created by the following programs:
i.	correlations80.do creates correlations.dta, which contains the following 
variables: corr gth_vareal nestab share sdgvar
ii.	correlations80iip.do: creates correlationsiip.dta which contains corriip 
gth_iip sdgthiip.
iii.	correlations80HPvareal.do: creates correlationsHPvareal.dta, which 
contains corrHPva.
iv.	correlations80_robust.do: creates correlations_robust.dta, which 
contains corr_rob
*	All the variables listed above are sorted by country and industry-pair and 
included in the main database detailed above.
2.	TRADE CREDIT MEASURES FOR EACH COUNTRY:
*	These set of programs take data from Worldscope (CD version 2005), 
Amadeus (2006), and the World Bank Investment Climate Assessments 
(ICAs) to create the various measures of country-level use of trade credit. 
They also compute the country-industry level measures used in the robustness 
analysis. Data from Worldscope and Amadeus is proprietary and not included. 
Data from the (ICAs) is included.
*	 Using data from Worldscope:
i.	create_tcreduse_measures_inv.do: produces 
Trade_credit_by_country_inv.dta, which contains InvPayturn1 and 
Stdbtpay.	
ii.	create_tcreduse_measures_regressions.do: creates the following two 
files
1.	Trade_credit_measures_medians_102008.dta, which contains 
InvPay, Std, InvPaymat, Matc2cgs.	
2.	Trade_credit_measures_regressions_inv.dta: creates INVPAY, 
STD	
iii.	create_tcreduse_measures_regressions_allsectors.do: creates 
Trade_credit_measures_medians_all.dta, which contains InvPay_all, 
Std_all.
*	Using data from Amadeus:
i.	create_tcreduse_measures_amadeus.do: creates 
Trade_credit_measures_medians_amadeus.dta, which contains 
InvPay_amadeus based on the 2003 version of the database.
ii.	create_tcreduse_measures_amadeus_2007.do: creates 
Trade_credit_measures_medians_amadeus_2007.dta, which contains 
InvPay_amadeus.
iii.	Final InvPay_amadeus included in the dataset is the one from the 2003 
version if available, otherwise the one from the 2007 version.
*	Using data from ICAs:
i.	create_tcredit_measures_from_coreica_2008.do: creates 
Trade_credit_use_by_country_ica_2006.dta, which contains 
Mcost2cgs_ica.
3.	TRADE CREDIT MEASURES FOR THE US:
*	There is only one program that takes data from Compustat (2003) and creates 
the representative measures over the period 1980-1989 or 1980-1999. The 
initial and final year to be considered are given as parameters at the beginning 
of the program. Compustat is also proprietary and not distributed as part of 
this documentation. The output databases are included.
*	trade_credit_102008.do: creates tcred_isic3_80891.dta that contains payturn, 
recturn, stdbtpay, and mcost2cgs which are the payables turnover, receivables 
turnover, short term debt to payables, material costs to costs of goods sold, 
and net payables turnover for each US industry during 1980-1989. The ratio 
of each of these measures to the average measure across industries is later 
denoted with an initial uppercase (Payturn, Recturn, Stdbtpay, and 
Mcost2cgs) and included in the database that is used to create the credit chain 
distances (see below)
4.	MEASURES OF CREDIT CHAIN DISTANCES:
*	There are two levels of these measures: i) the basic input-output linkages 
computed directly from US input output matrices, and (ii) the generic credit 
chain linkages, computed using the input-output linkages, and the relative use 
of trade credit from US industries (see point 3).
*	Basic input output linkages: These linkages are computed using data from the 
1992 US Benchmark IO matrices. These data is in the following text files:
*	use_matrix_isic_fin.txt: Use matrix (commodity by industry)
*	make_matrix_isic_fin.txt: Make matrix (industry by commodity)
*	tio_isic.txt: total industrial output vector
*	tdd_isic.txt: total domestic demand vector
*	tco_isic.txt: total consumption vector
*	va_isic.txt: total value added vector
*	These data is used by the Matlab program crea_distances.m, which produces 
as output the following series of text matrices:
*	COSTS: Cost matrix as described in the appendix
*	DEMS: Ultimate demand requirement matrix (D in the paper)
*	BUY and SELL: matrices with the buy and sell matrices as described 
in Conley and Dupor (2002).
*	Credit Chain linkages: The credit chain linkages are computed using the 
DEMS matrix and the (US) industry measures of relative trade credit use. To 
this end, the DEMS matrix computed by crea_distances.m was complemented 
with the industry-level measures of relative trade credit use and put in a stata 
dataset. Different datasets correspond to different measures of trade-credit 
use as follows:
*	Crea_model_matrices_cchains_inv.do: uses the database 
Cost_and_Dem_Matrices_with_TcredUSA.dta that contains DEMS 
and the industry level measures of relative trade credit use in the US 
(computed as described above). It produces the database 
Cost_and_Dem_model_matrices_CC_inv.dta that contains the 
following variables: DemPayCC_inv, DemStdpay_CC, 
DemPayCC_invmat.
*	Crea_model_matrices_by_country_Cchains_inv.do: uses the database 
Cost_and_Dem_Matrices_with_Tcred_bycty_05plus.dta that contains 
DEMS and the country-industry level measures produced using US 
data and Worldscope data when available for at least 5 companies in a 
country. It produces the file 
Cost_and_Dem_Model_matrices_bycty_05plus_CC_inv.dta that 
contains the variable DemInvPayCC_05
*	Crea_model_matrices_Cchains_UK_inv.do: uses the database 
Cost_and_Dem_Matrices_with_TcredUK.dta that contains DEMS 
computed using UK input output data in the same manner as that 
computed using US data. It produces 
Cost_and_Dem_Model_matrices_CC_UK_inv.dta that contains the 
variable DemPayCCUK_inv.
*	Crea_matrices_variances_by_country_Cchains.do: uses the database 
Cost_and_Dem_Matrices_with_Tcred_bycty_05plus.dta described 
above to produce Cost_and_Dem_Variance_matrices_bycty.dta that 
contains the variable DemVar
*	Crea_model_matrices_inv_withB.do: uses the file 
Cost_and_Dem_Matrices_with_TcredUSA.dta.dta described above to 
construct the database B_Model_matrices_inv.dta that contains the 
variable Bpay_inv
*	Crea_model_matrices_cchains_T.do: uses the file 
Cost_and_Dem_Matrices_with_TcredUSA.dta.dta described above to 
construct the database Cost_and_Dem_Model_matrices_CC_T.dta 
that contains the variable DemPayCC_test
*	Crea_back_fwd_matrices_cchains_inv.do: uses the database 
Backward_and_Forward_Matrices_with_TcredUSA.dta that contains 
measures of forward and backward linkages matrices (see paper) to 
create the file 
Backward_and_Forward_Model_matrices_CC_inv_net.dta that 
contains the variable BackwdPayCC.

